Field of the Invention
The present invention concerns a method and apparatus for automatically identifying a background region in order to facilitate delineation in a medical image of lesion.
Description of the Prior Art
When treating cancer using radiation or monitoring a tumor's response to the treatment, definition of gross tumor volume (GTV) is critical. GTV can be distinguished using anatomical imaging techniques such as CT or MRI. Functional imaging techniques such as PET or SPECT, on the other hand, can provide additional insight on the structure of the tumor and its metabolic activity which is used extensively as well in the treatment process. Metabolic activity may be expressed in terms of metabolic tumor volume or MTV.
Accurate shape and volume determination of lesions will help clinicians to reduce radiation damage to healthy tissues surrounding the lesion and deliver maximum radiation dose to the tumor. Accurate shape and volume determination of lesions will also help clinicians assess changes in metabolic volume in response to therapy more accurately. Therefore numerous studies have been performed on developing automated methods for tumor delineation. These delineation methods differ in terms of methodology but they often need an initialization which gives the algorithm some information about the lesion region and its background. Such initial information must to be provided by a user.
In a typical patient medical image, a lesion area is visible in the image, but the background area is prone to being defined very subjectively and therefore inconsistently. A lesion area would typically be visible, but the boundary with the background is typically not clear due to the resolution of the image, and image noise. These factors contribute to the variability in manual delineation. Furthermore, due to the complex shape of many background regions and the requirement to exclude non-background regions, the background area is time-consuming to create. In addition, the lesion delineation results produced by some algorithms may vary significantly depending on the initial background region definition. Such variation may affect the treatment planning substantially. Consistency in the background region is therefore needed. The present invention provides a solution for automated selection of the background region for automated lesion delineation.
Currently, the background region for automated lesion delineation is typically defined manually by the user by placing an ROI (region of interest) in a healthy region of an organ containing a lesion. This step makes the definition procedure user-dependent and time consuming for clinicians. Automatic delineation methods have the advantage of being less user-dependent, and methods that consider background uptake are typically more accurate than those that do not. However, the requirement to define a background region creates additional work for the clinician and introduces more subjectivity.
The ROI is typically a sphere or a rectangle because such shapes are easy to define with quick mouse interactions or similar. Other ROIs may have more complex shapes if certain regions of the image need to be avoided: for example, in the case of a lung lesion close to the diaphragm, the background region should include the lung but not the mediastinum or GI tract: this may not be possible with simple ROI spheres or rectangles, and therefore more complex shapes should be used, which is even more time consuming for the clinician.
Background prior art, which may assist in the understanding of the present invention, includes:
A. Schaefer, S. Kremp, D. Hellwig, C. Rübe, C.-M. Kirsch, and U. Nestle, “A contrast-oriented algorithm for FDG-PET-based delineation of tumor volumes for the radiotherapy of lung cancer: derivation from phantom measurements and validation in patient data.,” Eur. J. Nucl. Med. Mol. Imaging, vol. 35, no. 11, pp. 1989-99, Nov. 2008.
R. Boellaard, N. C. Krak, O. S. Hoekstra, and A. a Lammertsma, “Effects of noise, image resolution, and ROI definition on the accuracy of standard uptake values: a simulation study.,” J. Nucl. Med., vol. 45, no. 9, pp. 1519-27, Sep. 2004.